In many signal processing areas, and particularly in the area of airborne radar, it is desirable to perform fast fourier transforms (FFTs). FFTs are necessary to convert radar signal pulses received in the time domain to the frequency domain and back again. Many types of signal processing, including pulse compression decoding, can be done in the frequency domain more quickly.
In airborne radar systems, the signal processing equipment should be carried on board the airplane. However, space and power are strictly limited on board an aircraft. Accordingly, it is important to minimize the size and power consumption of the signal processing equipment. Since FFT engines constitute a substantial part of a radar system's signal processing equipment, it is important to simplify the mathematical operations required to perform FFTs as much as possible. This not only reduces the total amount of equipment required, but the cost of a digital radar system can also be reduced by using the same hardware for different operations and by using identical hardware for different systems.
Speed is also very important in airborne radar. A modern airplane and its targets fly quickly and collect vast amounts of radar information. In order for the aircraft crew to benefit from the information, it must be processed quickly enough for the crew to respond and quickly enough to make room for new information. The simpler the mathematical operations necessary to process the incoming information, the faster the processing can be performed.
Existing FFT engines, based most commonly on the Cooley-Tukey method, require a significant amount of hardware. Since FFTs must normally be performed several times in digital signal processing, this hardware constitutes a substantial part of the entire radar system. A meaningful reduction in the amount of hardware required and in the time it takes for the hardware to operate is of great benefit in the field.